Microsoft Azure Machine Learning
What is Microsoft Azure Machine Learning?
Machine Learning Studio is a powerfully simple browser-based, visual drag-and-drop authoring environment where no coding is necessary. Go from idea to deployment in a matter of clicks. Microsoft Azure Machine Learning Studio is a collaborative, drag-and-drop tool you can use to build, test, and deploy predictive analytics solutions on your data. Machine Learning Studio publishes models as web services that can easily be consumed by custom apps or BI tools such as Excel.
Company Details
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Real user data aggregated to summarize the product performance and customer experience.
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Product scores listed below represent current data. This may be different from data contained in reports and awards, which express data as of their publication date.
89 Likeliness to Recommend
100 Plan to Renew
85 Satisfaction of Cost Relative to Value
1
Since last award
Emotional Footprint Overview
Product scores listed below represent current data. This may be different from data contained in reports and awards, which express data as of their publication date.
+92 Net Emotional Footprint
The emotional sentiment held by end users of the software based on their experience with the vendor. Responses are captured on an eight-point scale.
How much do users love Microsoft Azure Machine Learning?
Pros
- Performance Enhancing
- Respectful
- Includes Product Enhancements
- Reliable
How to read the Emotional Footprint
The Net Emotional Footprint measures high-level user sentiment towards particular product offerings. It aggregates emotional response ratings for various dimensions of the vendor-client relationship and product effectiveness, creating a powerful indicator of overall user feeling toward the vendor and product.
While purchasing decisions shouldn't be based on emotion, it's valuable to know what kind of emotional response the vendor you're considering elicits from their users.
Footprint
Negative
Neutral
Positive
Feature Ratings
Model Training
Data Exploration and Visualization
Pre-Packaged AI/ML Services
Data Pre-Processing
Feature Engineering
Model Tuning
Performance and Scalability
Data Labeling
Model Monitoring and Management
Data Ingestion
Explainability
Vendor Capability Ratings
Breadth of Features
Ease of Data Integration
Quality of Features
Ease of Implementation
Ease of Customization
Availability and Quality of Training
Business Value Created
Ease of IT Administration
Product Strategy and Rate of Improvement
Usability and Intuitiveness
Vendor Support
Microsoft Azure Machine Learning Reviews
Ketan S.
- Role: Information Technology
- Industry: Engineering
- Involvement: IT Leader or Manager
Submitted Mar 2024
easy & quick to setup end-to-end AI/ML solutions
Likeliness to Recommend
What differentiates Microsoft Azure Machine Learning from other similar products?
1. Provide variety of services to successfully build any AI/ML solution easily for e.g Blob storage, visualization tools, BI tools, Model training & testing tools. 2. Additionally, we can share and collaborate with team on Azure itself which is really helpful when you are working in remote environment
What is your favorite aspect of this product?
I loved working the data labelling service. Web based UI makes it very easy to annotate data from anywhere and collaborate with the team. Also, various annotation shapes are available which makes it suitable for any business solution.
What do you dislike most about this product?
They don't have any AI recommendation services yet, which will make life of AI developer very easy.
What recommendations would you give to someone considering this product?
If you want quickly set up and make your AI environment up and running you should definitely give it a try. There will be a learning curve so as to understand the services , but once you are comfortable it will be worth it.
Pros
- Efficient Service
- Transparent
- Appreciates Incumbent Status
- Security Protects
Cons
- Slower Product Innovation
- Commodity Features
- Vendor Friendly Policies
Gaurav C.
- Role: Information Technology
- Industry: Technology
- Involvement: IT Development, Integration, and Administration
Submitted Mar 2024
Great tool for ML
Likeliness to Recommend
What differentiates Microsoft Azure Machine Learning from other similar products?
Microsoft Azure Machine Learning stands out for its seamless integration with the broader Microsoft ecosystem, offering easy connectivity with Azure services like storage, databases, and analytics tools. Its comprehensive suite includes automated machine learning capabilities, enabling users to build, train, and deploy models efficiently
What do you dislike most about this product?
One potential drawback of Microsoft Azure Machine Learning is its complexity, especially for newcomers to the platform. Navigating through its various components and understanding how they interact can be challenging initially.
What recommendations would you give to someone considering this product?
For those considering Microsoft Azure Machine Learning, I'd recommend starting with thorough documentation and tutorials provided by Microsoft to grasp the platform's fundamentals. Collaborating with experienced practitioners or seeking community support can also expedite the learning process and help navigate complex scenarios effectively.
Pros
- Continually Improving Product
- Reliable
- Enables Productivity
- Trustworthy
Avinash G.
- Role: Information Technology
- Industry: Technology
- Involvement: IT Development, Integration, and Administration
Submitted Mar 2024
Really awesome service easy to use
Likeliness to Recommend
What differentiates Microsoft Azure Machine Learning from other similar products?
Azure service is mind blowing it's GPU power and all the services that provided by azure
What is your favorite aspect of this product?
Service for AI integration and some High GPU processing
What do you dislike most about this product?
There is nothing to dislike but pricing is little bit more but anyway I don't mind it and really like it
What recommendations would you give to someone considering this product?
If you're building large AI model or ML model go for it
Pros
- Helps Innovate
- Continually Improving Product
- Reliable
- Performance Enhancing